Job Responsibilities:
1. Responsible for building and maintaining the mechanisms for running model inference.
2. Work with other teams to get new models from design to production as efficiently as possible.
3. Make technical decisions that balance performance and cost.
4. Contribute to best practices, design patterns and identifying opportunities to refactor code.
5. Collaborate across teams to ensure the full video pipeline is efficient.
6. Maintain the CI/CD pipeline to ensure rapid deployment of models.
7. Take an active role in building, maintaining the inference edge device along with the tools required to monitor it in the field.
8. Support other Vision Engineers in learning existing design concepts.
9. Maintain documentation to allow others to further develop inference components.
10. Plays an active role in team process improvements.
11. Create and maintain mechanisms to deploy models across multiple deployment targets.
12. Work with the team lead to scope and refine data requirements and to influence technical decisions, from problem statement to delivered solution.
13. Work with internal stakeholders to ensure new algorithm ideas get delivered into production.
14. Create prototypes that help achieve business Objectives and Key Responsibilities (OKRs).
15. Work with the technical ops team to help onboard and adapt farm installs where required.
16. Create new ways to run algorithms effectively.
Your Profile / Qualifications:
1. Degree in Computer Science or related computer vision based discipline.
2. Experience taking models from creation to production.
3. Experience working with academics/researchers to convert ideas to products.
4. A comprehensive understanding of model inference.
5. Experience with both cloud inference and edge inference devices.
6. Detailed knowledge of Python.
7. Understanding of image and video processing.
8. Driven by high performance.
9. Eagerness to stay up to date with the latest technologies.
#J-18808-Ljbffr